Best AI Models for Intel Arc A770 16GB

Runs 14B models well; 27–31B only just fits.

16 GB GDDR6560 GB/s131 TFLOPS FP16225 WAlchemist 2022

What LLMs can the Arc A770 16GB run?

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.0 t/s	44.0 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 85.9 t/s	85.9 tok/s	Q4_K_M · 3.4 GB
3	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 71.2 t/s	71.2 tok/s	Q4_K_M · 13.1 GB
4	Phi 4Microsoft Q4_K_M · 12.5 GB · 29.4 t/s	29.4 tok/s	Q4_K_M · 12.5 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.0 t/s	34.0 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Coding Score	Quant · VRAM
1	GPT OSS 20BOpenAIHow to run → Q4_K_M · 13.1 GB · 71.2 t/s	71.2 tok/s		Q4_K_M · 13.1 GB
2	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 52.8 t/s	52.8 tok/s		Q4_K_M · 7.9 GB
3	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 44.0 t/s	44.0 tok/s	overall	Q4_K_M · 6.6 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.0 t/s	34.0 tok/s		Q4_K_M · 9.0 GB
5	Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 123 t/s	123 tok/s		Q4_K_M · 5.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.0 t/s	44.0 tok/s	Q4_K_M · 6.6 GB
2	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 71.2 t/s	71.2 tok/s	Q4_K_M · 13.1 GB
3	Qwen3 8BAlibaba Q4_K_M · 7.6 GB · 50.7 t/s	50.7 tok/s	Q4_K_M · 7.6 GB
4	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 52.8 t/s	52.8 tok/s	Q4_K_M · 7.9 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.0 t/s	34.0 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.0 t/s	44.0 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 85.9 t/s	85.9 tok/s	Q4_K_M · 3.4 GB
3	Mistral Nemo Instruct 2407Mistral AI Q4_K_M · 11.0 GB · 34.7 t/s	34.7 tok/s	Q4_K_M · 11.0 GB
4	Llama 3.1 8B InstructMeta Q4_K_M · 7.9 GB · 52.8 t/s	52.8 tok/s	Q4_K_M · 7.9 GB
5	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.0 t/s	34.0 tok/s	Q4_K_M · 9.0 GB

#	Model	Speed ↓	Quant · VRAM
1	Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 85.9 t/s	85.9 tok/s	Q4_K_M · 3.4 GB
2	GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 71.2 t/s	71.2 tok/s	Q4_K_M · 13.1 GB
3	Qwen3.5 9BAlibaba Q4_K_M · 6.6 GB · 44.0 t/s	44.0 tok/s	Q4_K_M · 6.6 GB
4	Gemma 4 12B ITGoogle Q4_K_M · 9.0 GB · 34.0 t/s	34.0 tok/s	Q4_K_M · 9.0 GB
5	Phi 4Microsoft Q4_K_M · 12.5 GB · 29.4 t/s	29.4 tok/s	Q4_K_M · 12.5 GB

#	Model	Speed	Quant · VRAM
1	Qwen3.5 9BAlibabaHow to run → Q4_K_M · 6.6 GB · 44.0 t/s	44.0 tok/s	Q4_K_M · 6.6 GB
2	Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 85.9 t/s	85.9 tok/s	Q4_K_M · 3.4 GB
3	Gemma 3 12B ITGoogle Q4_K_M · 10.9 GB · 34.8 t/s	34.8 tok/s	Q4_K_M · 10.9 GB
4	Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 98.6 t/s	98.6 tok/s	Q4_K_M · 5.0 GB
5	MiMo V2.6 Distill Qwen 9BXiaomi Q4_K_M · 6.5 GB · 45.1 t/s	45.1 tok/s	Q4_K_M · 6.5 GB

See all 307 models on the Arc A770 16GB →Best quant that fits · speeds estimated on this card

About the Arc A770 16GB

The Arc A770 16GB is an entry card in the 16 GB class: it runs 14B models well. It is power-hungry for its speed, and at its $349 MSRP it gave the best speed per dollar of the cards compared. Alchemist generation, released 2022.

Speed in 16 GB#14560 GB/s

Per watt#110.20 tok/s per W on Qwen3.5 9B (9B params)

Per dollar#112.6 tok/s per $100 on Qwen3.5 9B (9B params)

GenerationAlchemistreleased 2022

Arc A770 16GB strengths and weaknesses

Strengths

Runs 35B MoE models: Qwen3.6 35B A3B at 65.0 tok/s in 15.7 GB

Weaknesses

70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 16 GB here
oneAPI, not CUDA: No FP8 or NVFP4 weights and no vLLM AWQ or GPTQ; use GGUF builds

Speed per dollar and per watt

NewUsed

On Qwen3.5 9B (9B params) at Q4_K_M. New prices are compared with new, used with used. The last two columns are the speed you get per $100 of price and per 100 W of board power; higher is better. The Arc A770 16GB has no current price, so it is shown at its MSRP.

Card	New price	tok/s	tok/s per $100	tok/s per 100 W
Arc A770 16GB16 GB	about $349	44.0	12.6	19.6
RTX 507012 GB	about $840	68.7	8.2	27.5
RX 7900 XTX24 GB	about $1,130	90.6	8.0	25.5
RTX 5070 Ti16 GBBest new value	about $1,170	91.6	7.8	30.5
RX 907016 GB	about $800	60.4	7.6	27.5
RX 9070 XT16 GB	about $815	60.4	7.4	19.9
RTX 508016 GB	about $1,690	98.1	5.8	27.3
RX 9060 XT 16GB16 GB	about $590	30.2	5.1	18.9

Card	Used price	tok/s	tok/s per $100	tok/s per 100 W
RTX 3060 12GB12 GBBest used value	about $329	36.8	11.2	21.6
RX 907016 GB	about $650	60.4	9.3	27.5
RX 7900 XTX24 GB	about $1,000	90.6	9.1	25.5
RTX 407012 GB	about $575	51.5	9.0	25.8
RTX 5070 Ti16 GB	about $1,100	91.6	8.3	30.5
RTX 4070 Ti SUPER16 GB	about $900	68.7	7.6	24.1
RTX 4070 SUPER12 GB	about $675	51.5	7.6	23.4
RTX 4070 Ti12 GB	about $722	51.5	7.1	18.1

Similar GPUs

Cards people weigh against the Arc A770 16GB, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.

37% faster, same 16 GBRX 9070AMD · 16 GB · RDNA 4

▲ 37% speedsame 16 GB$800

56% faster, same 16 GBRTX 4070 Ti SUPERNVIDIA · 16 GB · Ada Lovelace

▲ 56% speedsame 16 GB$799rent $0.16/hr

8 GB more and nearly 2× the speedRX 7900 XTXAMD · 24 GB · RDNA 3

▲ 106% speed▲ 8 GB$1,130

4 GB more and 72% fasterRX 7900 XTAMD · 20 GB · RDNA 3

▲ 72% speed▲ 4 GB$899

More efficient per wattRTX 5090 Laptop GPUNVIDIA · 24 GB · Blackwell

▲ 108% speed▲ 8 GB

Best value near the Arc A770 16GBRTX 5070 TiNVIDIA · 16 GB · Blackwell

▲ 108% speedsame 16 GB$1,170rent $0.17/hr

Arc A770 16GB tokens per second by model size

Output speed depends on memory bandwidth (560 GB/s). Grey rows need more than 16 GB.

9BQwen3.5 9B · Q4_K_M · 6.6 GB
44.0tok/s
14BQwen3 14B · Q4_K_M · 11.9 GB
29.5tok/s
27–31BQwen3.8 27B · Q3_K_L · 15.4 GB tight · Q3_K_L
18.7tok/s
35B MoEQwen3.6 35B A3B · IQ3_S · 15.7 GB tight · IQ3_S
65.0tok/s
70BLlama 3.3 70B Instruct · not at 4-bit
needs 51.3 GB
120B MoEGPT OSS 120B · not at 4-bit
needs 70.8 GB

Estimated speeds: Q4_K_M, 4K context, one user. How we estimate

All 307 models on the Arc A770 16GB

Featured only

Best quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with Intel Arc A770 16GB — ranked by Score, recency and Fit
Model	Quant	VRAM	Speed	Context	Fit
Qwen3.5 9B9.7BVisionFunctions Q4_K_M·44.0 t/s	Q4_K_M	6.6 GB41%	44.0 t/s	262K	A77, Runs well
Qwen3.8 27B27.8BVisionFunctions Q3_K_L·18.7 t/s	Q3_K_L	15.4 GB97%	18.7 t/s	262K	C32, Usable
Gemma 4 26B A4B IT25.8BVisionFunctions Q4_K_S·65.7 t/s	Q4_K_S	15.5 GB97%	65.7 t/s	262K	B59, Decent
Gemma 4 12B IT12.0BChatFunctions Q4_K_M·34.0 t/s	Q4_K_M	9.0 GB56%	34.0 t/s	262K	A73, Runs well
GPT OSS 20B20.9BChatFunctions Q4_K_M·71.2 t/s	Q4_K_M	13.1 GB82%	71.2 t/s	131K	A83, Runs well
Ling 3.0 Tiny7.9BChatFunctions Q4_K_M·122.9 t/s	Q4_K_M	5.5 GB34%	122.9 t/s	131K	S95, Runs great
MiMo V2.6 Distill Qwen 9B9.4BVisionCodeFunctions Q4_K_M·45.1 t/s	Q4_K_M	6.5 GB41%	45.1 t/s	262K	A77, Runs well
Muse Glimmer 30B29.8BVision IQ3_M·20.2 t/s	IQ3_M	15.1 GB95%	20.2 t/s	131K	C38, Usable
MiniCPM5 2B2.5BChatFunctions Q4_K_M·147.4 t/s	Q4_K_M	2.5 GB16%	147.4 t/s	131K	S97, Runs great
Qwen3.5 4B4.7BVisionFunctions Q4_K_M·85.9 t/s	Q4_K_M	3.4 GB21%	85.9 t/s	262K	S88, Runs great
Spark X2.6 4B4.1BChatFunctions Q4_K_M·94.6 t/s	Q4_K_M	4.3 GB27%	94.6 t/s	1049K	S90, Runs great
LFM2.5 24B A2B24.0BChatFunctions Q4_K_M·74.5 t/s	Q4_K_M	15.0 GB94%	74.5 t/s	131K	B62, Decent
Ornith 1.5 9B9.7BChatFunctions Q4_K_M·44.0 t/s	Q4_K_M	6.6 GB41%	44.0 t/s	262K	A77, Runs well
MiniCPM V 4.7 1B1.6BVisionFunctions Q4_K_M·218.8 t/s	Q4_K_M	1.6 GB10%	218.8 t/s	262K	S100, Runs great
LFM3 1.7B1.7BChatFunctions Q4_K_M·194.4 t/s	Q4_K_M	2.1 GB13%	194.4 t/s	262K	S99, Runs great

Arc A770 16GB specs, power and PSU

Specs

Architecture: Alchemist
VRAM: 16 GB GDDR6
Memory bandwidth: 560.0 GB/s
FP16 (dense): 131.00 TFLOPS
TDP: 225 W
Released: 2022-10-12
MSRP: $349

Arc A770 16GB FAQ

Is the Arc A770 16GB still worth it in 2026?

At its MSRP of $349 you get 12.6 tok/s per $100 on Qwen3.5 9B, which ranks 1st of the 8 cards compared here; it is also the 14th fastest out of 17 cards with 16 GB. It runs 14B models well; 27–31B only just fits.

What is the largest model the Arc A770 16GB can run?

Gemma 4 26B A4B IT (25.8B) is the largest at 4-bit or better: at Q4_K_S it uses 15.5 GB of 16 GB, and runs at about 65.7 tok/s. At 3-bit, a bigger model fits too: Gemma 2 27B IT (27.2B) at IQ3_M, 15.0 GB.

Can the Arc A770 16GB run Qwen3.5 9B?

Yes. Qwen3.5 9B fits at Q4_K_M, using 6.6 GB of 16 GB, and it is the best model that runs well on this card.

Can the Arc A770 16GB run 70B models?

No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 16 GB on this card.

How many tokens per second does the Arc A770 16GB give?

About 44.0 tok/s on Qwen3.5 9B at Q4_K_M, with the first token after 3.4 s on a 4K-token prompt.

What power supply does the Arc A770 16GB need?

Plan a 450 W PSU (2× the 225 W TDP).

Is 16 GB enough for coding and agents?

Yes for coding: GPT OSS 20B, the best of the 2 coding models that fit, runs at about 71 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.

Is renting cheaper than buying an Arc A770 16GB?

An RTX 3090 (24 GB) rents from $0.17/hr. Renting costs as much as buying after ≈2,100 hours (≈1.4 years at 4 h a day).

Best coding LLMs 16 GB VRAM 24 GB VRAM GPUs with 16 GB or more RTX 5090 RTX 3090 Ti